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Record W1486167929

From Enlistment to the Grave: The Impact of the First World War on 52 Canadian Soldiers

2000· article· en· W1486167929 on OpenAlexaffabout
Mike Wert

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsHistoryWorld War IIPolitical scienceEconomic historyDemographySociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Because they have clearly demarcated beginnings and endings, wars tend to be studied in isolation. Studies are made of the events leading up to wars, the wars themselves, and their aftermaths as though each could be easily pigeon-holed. The majority of work done on the First World War, for example, has concerned itself solely with the events of 1914-1918, as though the war ended with the Armistice. What this approach forgets is that wars exact a profound and lasting influence on those who live through them. For many—and in particular for many veterans—the Great War did not end with the cessation of hostilities, it continued to influence the rest of their lives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.947

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0420.009
Scholarly communication0.0060.002
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0160.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.213
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2000
Admission routes2
Has abstractyes

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